Author

R. R. Baghbadorani

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Preprint Oct 2026

Learning in Inverse Games: Tractable Training with Probabilistic Guarantees

Inverse game theory seeks to learn agents'unknown objectives from observed equilibrium behavior. Existing residual-based approaches can lead to non-convex problems and need not ensure strong monotonicity of the learned game, limiting reliable equilibrium prediction. We develop a tractable convex framework for learning...

Arghya Mallick, R. R. Baghbadorani, Peyman Mohajerin Esfahani et al. · 0 citations

Preprint Jul 2026

Dynamic Congestion Pricing in Distribution Networks via a Convex-Analytic Bilevel Reformulation

Dynamic congestion pricing is an important tool for managing congestion and coordinating distributed energy resources in active distribution networks. However, scalable mechanisms that preserve participant autonomy remain computationally challenging because the operator-resource interaction is naturally bilevel. This p...

R. R. Baghbadorani, Ali Nikseresht, J. Cho et al. · 0 citations